Energy-Efficient Load Balancing Ant Based Routing Algorithm for Wireless Sensor Networks

Xinlu Li, Brian Keegan, Fredrick Mtenzi, Thomas Weise, Ming Tan

Research output: Contribution to journalArticlepeer-review

97 Citations (Scopus)

Abstract

Wireless Sensor Networks (WSNs) are a type of self-organizing networks with limited energy supply and communication ability. One of the most crucial issues in WSNs is to use an energy-efficient routing protocol to prolong the network lifetime. We therefore propose the novel Energy-Efficient Load Balancing Ant-based Routing Algorithm (EBAR) for WSNs. EBAR adopts a pseudo-random route discovery algorithm and an improved pheromone trail update scheme to balance the energy consumption of the sensor nodes. It uses an efficient heuristic update algorithm based on a greedy expected energy cost metric to optimize the route establishment. Finally, in order to reduce the energy consumption caused by the control overhead, EBAR utilizes an energy-based opportunistic broadcast scheme. We simulate WSNs in different application scenarios to evaluate EBAR with respect to performance metrics such as energy consumption, energy efficiency, and predicted network lifetime. The results of this comprehensive study show that EBAR provides a significant improvement in comparison to the state-of-the-art approaches EEABR, SensorAnt, and IACO.

Original languageEnglish
Article number8794794
Pages (from-to)113182-113196
Number of pages15
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • Ant colony optimization
  • energy efficiency
  • load balancing
  • routing algorithm
  • wireless sensor networks

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